亞實(shí)性肺結(jié)節(jié)CT閾值分割：實(shí)性成分識(shí)別與定量
發(fā)布時(shí)間：2018-11-23 12:58
【摘要】：背景與目的在胸部計(jì)算機(jī)斷層掃描(computed tomography,CT)圖像上肺內(nèi)亞實(shí)性結(jié)節(jié)(subsolid nodule,SSN)是指純磨玻璃結(jié)節(jié)和部分實(shí)性結(jié)節(jié)。SSN實(shí)性成分的識(shí)別與定量對(duì)鑒別診斷,預(yù)測(cè)病理和評(píng)估預(yù)后具有重要價(jià)值,但目前缺乏公認(rèn)且客觀的標(biāo)準(zhǔn)。對(duì)亞實(shí)性結(jié)節(jié)內(nèi)實(shí)性成分做CT體積定量的研究報(bào)告尚少。本研究旨在探究CT閾值分割法判斷SSN類(lèi)型并定量其實(shí)性成分體積的閾值。方法共納入102例SSN。由觀察者1和觀察者2分別獨(dú)立對(duì)結(jié)節(jié)內(nèi)有無(wú)實(shí)性成分,即結(jié)節(jié)的類(lèi)型(部分實(shí)性或純磨玻璃)進(jìn)行主觀判斷,結(jié)果不一致時(shí)采納觀察者3的意見(jiàn),由此確定出所有結(jié)節(jié)的類(lèi)型并以此作為評(píng)估閾值分割法判斷SSN類(lèi)型效能的參照標(biāo)準(zhǔn)。被判定為部分實(shí)性的結(jié)節(jié)由觀察者1和觀察者2分別獨(dú)立對(duì)其實(shí)性成分進(jìn)行體積測(cè)量,測(cè)量時(shí)借助Auto Contour軟件包并輔以手動(dòng)調(diào)整。以?xún)晌挥^察者所得實(shí)性成分體積的平均值作為評(píng)估閾值分割法定量SSN實(shí)性成分體積的參照標(biāo)準(zhǔn)。由觀察者1對(duì)全部結(jié)節(jié)進(jìn)行閾值分割,步驟為首先采用Auto Contour軟件包對(duì)結(jié)節(jié)進(jìn)行整體提取并記錄結(jié)節(jié)的整體體積,然后使用3D-color-ROI工具計(jì)算所獲結(jié)節(jié)內(nèi)不同CT值區(qū)間的體素體積。共設(shè)9個(gè)CT值區(qū)間,下限值(閾值)分別設(shè)為-500 HU、-450 HU、-400HU、-350 HU、-300HU、-250 HU、-200 HU、-160 HU、-130 HU,上限值均設(shè)為2000 HU,假定上述CT值區(qū)間的體素均為實(shí)性成分。計(jì)算閾值分割所獲實(shí)性成分體積與結(jié)節(jié)整體體積的比率(%)。以觀察者確定的結(jié)節(jié)類(lèi)型為狀態(tài)變量,以體積比率為檢驗(yàn)變量,繪制不同CT值區(qū)間判斷結(jié)節(jié)類(lèi)型的受試者工作特征(receiver operating characteristic,ROC)曲線,得到曲線下面積(area under curve,AUC)。應(yīng)用DeLong檢驗(yàn)篩選CT閾值分割判斷SSN類(lèi)型的閾值。通過(guò)最大Youden指數(shù)得到確認(rèn)結(jié)節(jié)存在實(shí)性成分的體積比率界限值。對(duì)閾值分割所得體積與實(shí)性成分體積參照標(biāo)準(zhǔn)之間進(jìn)行配對(duì)Wilcoxon檢驗(yàn),篩選可用于實(shí)性成分體積定量的閾值。結(jié)果閾值為-250 HU時(shí)判斷亞實(shí)性結(jié)節(jié)類(lèi)型的準(zhǔn)確度最高(AUC=0.982),對(duì)應(yīng)體積比率界限值為1.10%,此時(shí)敏感度、特異度分別為100.0%、89.7%;閾值為-300 HU時(shí)判斷亞實(shí)性結(jié)節(jié)類(lèi)型的準(zhǔn)確度次之(AUC=0.977),對(duì)應(yīng)體積比率界限值為6.14%,此時(shí)敏感度、特異度分別為90.5%、94.9%。然而閾值-250 HU與閾值-350 HU、-300 HU、-200 HU、-160 HU、-130 HU在判斷亞實(shí)性結(jié)節(jié)類(lèi)型上差異不顯著(P均0.05)。閾值為-250 HU、-300 HU時(shí)所得實(shí)性成分體積202.7mm~3(598.2 mm~3)、247.1 mm~3(696.0 mm~3)與參照標(biāo)準(zhǔn)199.5 mm~3(743.1 mm~3)間無(wú)顯著差異(P=0.1251、0.0613),而其他閾值所得實(shí)性成分體積均與參照標(biāo)準(zhǔn)間存在顯著差異(P均0.05)。結(jié)論本研究表明,CT閾值分割能夠可靠地對(duì)SSN的類(lèi)型進(jìn)行判斷并對(duì)其實(shí)性成分體積進(jìn)行定量評(píng)估;閾值可設(shè)為-250 HU或-300 HU。
[Abstract]:Background & objective on chest computed tomography (computed tomography,CT) images, subsolid pulmonary nodules (subsolid nodule,SSN) are pure ground glass nodules and partial solid nodules. It is important to predict pathology and evaluate prognosis, but there is a lack of accepted and objective criteria. There are few studies on CT volume quantification of solid components in subsolid nodules. The purpose of this study was to explore the threshold value of CT threshold segmentation to determine the SSN type and to quantify the volume of the actual component. Methods 102 cases of SSN. were included Observer 1 and Observer 2 made independent subjective judgments on whether there were solid components in the nodules, that is, the types of nodules (partially solid or pure ground glass). When the results were inconsistent, the opinion of Observer 3 was adopted. The types of all nodules are determined and used as a reference criterion for evaluating the effectiveness of SSN type by threshold segmentation method. The nodules determined to be partially solid were measured independently by Observer 1 and Observer 2, respectively, with the help of Auto Contour software package and manual adjustment. The mean value of real component volume obtained by two observers is used as the reference criterion for evaluating the volume of SSN real component by threshold segmentation method. The threshold value of all the nodules was segmented by observer 1. The steps were as follows: firstly, the whole nodules were extracted by Auto Contour software package and the whole volume of the nodules was recorded. Then the volume of voxel in different CT values of the nodules was calculated by using the 3D-color-ROI tool. There are 9 CT ranges, and the lower limit (threshold) is -500 HU,-450 HU,-400HU,-350 HU,-300HU,-250 HU,-200 HU,-160 HU,-130 HU, and the upper limit is 2000 HU,. It is assumed that the voxels in the above CT interval are real components. Calculate the ratio of the solid component volume to the whole nodule volume obtained by threshold segmentation (%). Taking the nodular type determined by the observer as the state variable and the volume ratio as the test variable, the (receiver operating characteristic,ROC curves with different CT values to judge the nodule type were drawn, and the area under the curve (area under curve,AUC) was obtained. DeLong test was used to select the threshold value of CT to judge the threshold of SSN type. By using the maximum Youden exponent, the boundary value of the volume ratio is obtained to confirm the existence of solid components in the nodules. The matched Wilcoxon test was performed between the volume of real component and the reference standard of real component volume, and the threshold value for quantitative quantification of real component volume was screened. Results when the threshold was -250 HU, the accuracy (AUC=0.982) of subsolid nodules was the highest, and the threshold value of the corresponding volume ratio was 1.10. The sensitivity and specificity were 100.0 and 89.7, respectively. When the threshold was -300 HU, the accuracy (AUC=0.977) of subsolid nodules was the second, and the corresponding threshold value of volume ratio was 6.14. At this time, the sensitivity and specificity were 90.5 and 94.9, respectively. However, there was no significant difference between the threshold of-250 HU and the threshold of-350 HU,-300 HU,-200 HU,-160 HU,-130 HU in the classification of subsolid nodules. There was no significant difference between 202.7mm~3 (598.2 mm~3), 247.1 mm~3 (696.0 mm~3) and 199.5 mm~3 (743.1 mm~3) when the threshold was -250 HU,-300 HU. However, the volume of solid components obtained from other thresholds was significantly different from that of reference standard (P 0.05). Conclusion this study shows that CT threshold segmentation can reliably judge the type of SSN and quantitatively evaluate the volume of actual components, and the threshold can be set to -250 HU or -300 HU..
【學(xué)位授予單位】：天津醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R734.2;R730.44
本文編號(hào)：2351704
[Abstract]:Background & objective on chest computed tomography (computed tomography,CT) images, subsolid pulmonary nodules (subsolid nodule,SSN) are pure ground glass nodules and partial solid nodules. It is important to predict pathology and evaluate prognosis, but there is a lack of accepted and objective criteria. There are few studies on CT volume quantification of solid components in subsolid nodules. The purpose of this study was to explore the threshold value of CT threshold segmentation to determine the SSN type and to quantify the volume of the actual component. Methods 102 cases of SSN. were included Observer 1 and Observer 2 made independent subjective judgments on whether there were solid components in the nodules, that is, the types of nodules (partially solid or pure ground glass). When the results were inconsistent, the opinion of Observer 3 was adopted. The types of all nodules are determined and used as a reference criterion for evaluating the effectiveness of SSN type by threshold segmentation method. The nodules determined to be partially solid were measured independently by Observer 1 and Observer 2, respectively, with the help of Auto Contour software package and manual adjustment. The mean value of real component volume obtained by two observers is used as the reference criterion for evaluating the volume of SSN real component by threshold segmentation method. The threshold value of all the nodules was segmented by observer 1. The steps were as follows: firstly, the whole nodules were extracted by Auto Contour software package and the whole volume of the nodules was recorded. Then the volume of voxel in different CT values of the nodules was calculated by using the 3D-color-ROI tool. There are 9 CT ranges, and the lower limit (threshold) is -500 HU,-450 HU,-400HU,-350 HU,-300HU,-250 HU,-200 HU,-160 HU,-130 HU, and the upper limit is 2000 HU,. It is assumed that the voxels in the above CT interval are real components. Calculate the ratio of the solid component volume to the whole nodule volume obtained by threshold segmentation (%). Taking the nodular type determined by the observer as the state variable and the volume ratio as the test variable, the (receiver operating characteristic,ROC curves with different CT values to judge the nodule type were drawn, and the area under the curve (area under curve,AUC) was obtained. DeLong test was used to select the threshold value of CT to judge the threshold of SSN type. By using the maximum Youden exponent, the boundary value of the volume ratio is obtained to confirm the existence of solid components in the nodules. The matched Wilcoxon test was performed between the volume of real component and the reference standard of real component volume, and the threshold value for quantitative quantification of real component volume was screened. Results when the threshold was -250 HU, the accuracy (AUC=0.982) of subsolid nodules was the highest, and the threshold value of the corresponding volume ratio was 1.10. The sensitivity and specificity were 100.0 and 89.7, respectively. When the threshold was -300 HU, the accuracy (AUC=0.977) of subsolid nodules was the second, and the corresponding threshold value of volume ratio was 6.14. At this time, the sensitivity and specificity were 90.5 and 94.9, respectively. However, there was no significant difference between the threshold of-250 HU and the threshold of-350 HU,-300 HU,-200 HU,-160 HU,-130 HU in the classification of subsolid nodules. There was no significant difference between 202.7mm~3 (598.2 mm~3), 247.1 mm~3 (696.0 mm~3) and 199.5 mm~3 (743.1 mm~3) when the threshold was -250 HU,-300 HU. However, the volume of solid components obtained from other thresholds was significantly different from that of reference standard (P 0.05). Conclusion this study shows that CT threshold segmentation can reliably judge the type of SSN and quantitatively evaluate the volume of actual components, and the threshold can be set to -250 HU or -300 HU..
【學(xué)位授予單位】：天津醫(yī)科大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R734.2;R730.44
【參考文獻(xiàn)】
相關(guān)期刊論文 前1條
1 王群;蔣偉;奚俊杰;;肺部多發(fā)磨玻璃影的外科治療[J];中國(guó)肺癌雜志;2016年06期
，本文編號(hào)：2351704
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